Evidence map›Paper›PMID 41451325›Full record

ArticleFrontiers in artificial intelligence2025

Exploring the use and perceived impact of artificial intelligence in medical internship: a cross-sectional study of Palestinian doctors.

Abdallah Qawasmeh, Salahaldeen Deeb, Alhareth M Amro, Khaled Alhashlamon, Ibrahim Althaher, Nour Yaser Mohammad Shadeed, Khadija Mohammad, Farid K Abu Shama

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Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Abdallah QawasmehHealth Education and Scientific Research Unit, Minstry of Health, Ramallah, Palestine.
Salahaldeen DeebFaculty of Medicine, Al-Quds University, Jerusalem, Palestine.
Alhareth M AmroFaculty of Medicine, Al-Quds University, Jerusalem, Palestine.
Khaled AlhashlamonFaculty of Medicine, Al-Quds University, Jerusalem, Palestine.
Ibrahim AlthaherFaculty of Medicine, Al-Quds University, Jerusalem, Palestine.
Nour Yaser Mohammad ShadeedHealth Education and Scientific Research Unit, Minstry of Health, Ramallah, Palestine.
Khadija MohammadHealth Education and Scientific Research Unit, Minstry of Health, Ramallah, Palestine.
Farid K Abu ShamaHealth Education and Scientific Research Unit, Minstry of Health, Ramallah, Palestine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) is increasingly used in medical education to support academic learning, clinical competence, and efficiency. However, the extent and impact of AI usage among medical interns, particularly in Palestine, remain underexplored. Objective: This study aimed to assess the prevalence of AI usage among internship doctors in Palestine and evaluate its perceived impact on their academic performance, clinical competence, time management, and research skills. Methods: A cross-sectional survey was conducted with 307 internship doctors in Palestine. The survey collected data on the frequency and types of AI tools used, including ChatGPT, and interns' perceptions of AI's impact on their training. Demographic information, such as age, gender, and university affiliation, was also gathered to explore potential associations with AI usage patterns. Results: The study found that 76.9% of interns used AI regularly, with ChatGPT being the most popular tool (76.2%). Despite frequent use, only 3.3% reported formal AI training. The majority of interns perceived AI as beneficial in improving academic performance (61%), clinical competence (67%), and time management (74%). Notably, time management showed the highest perceived improvement. However, 75.9% expressed concerns about becoming overly reliant on AI, fearing it could diminish critical thinking and clinical judgment. Age and university affiliation were associated with differences in AI usage patterns and perceived benefits, with older interns and those from international universities reporting greater perceived improvements. Conclusion: This cross-sectional study highlights the widespread use of AI among internship doctors in Palestine and generally positive perceptions of its educational value, particularly for academic performance and clinical competence. However, it also reveals a substantial gap in formal AI training, suggesting a need for structured, ethically grounded AI education in medical curricula. Because the study is exploratory and cross-sectional, these findings should be interpreted as perceived associations rather than evidence that AI use or training causes improved outcomes; future longitudinal and interventional studies are needed to clarify long term effects.

Indexed as

academic performanceartificial intelligenceclinical competenceinternship doctorsmedical educationtime management

Identifiers

PMID41451325
PMCPMC12727930

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.